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Weakly supervised probabilistic atlas generation through multi-atlas label fusion

  • US 10,169,873 B2
  • Filed: 03/23/2017
  • Issued: 01/01/2019
  • Est. Priority Date: 03/23/2017
  • Status: Active Grant
First Claim
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1. A method to detect anatomical region of interest (ROI) from training images having class labels to help image classification performance, the method comprising:

  • (a) receiving, as input, a plurality of images, each image in the plurality of images having a class label 1≤

    l≤

    L and a positive threshold th between 0 and 1 for use with discriminative score maps;

    (b) computing a discriminative score map for each image in the plurality of images using all remaining images as training images, where the discriminative score map for a given image comprises a spatial varying discriminative score for each image location within the given image;

    (c) for each class label l, smoothing any of the discriminative score maps produced for images with the label l;

    (d) producing a region of interest mask for each image in the plurality of images by thresholding its discriminative score map by th such that the produced mask has value 1 for pixels with discriminative scores greater than th and 0, otherwise; and

    (e) performing image classification based on region of interest masks identified in (d).

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